车载社交网络中社会感知的高效数据传输策略

As a result of the convergence of vehicular networks and social networks, vehicular social networks are an emerging area that is attracting more and more attention. Efficient data delivery plays a critically important role in vehicular social applications. However, vehicular social networks typically operate in dynamic, hybrid environments, and in large scale. These characteristics give rise to a large number of significant challenges facing efficient data delivery. Among many others, timeliness and reliability guarantee, resource efficiency improvement, and differentiated service provision are three important challenges that remain to be addressed. With focus on these issues, this project will deal with efficient data delivery schemes that can be used in vehicular social networks. Based on the idea of socially-aware networking, a series of socially-aware data delivery mechanisms will be developed to achieve efficient data delivery with high delivery success ratio, short delivery delay, and high resource efficiency. Specifically, this project will propose broadcasting algorithms that take advantage of temporal multilayer network theory. These algorithms will facilitate real-time broadcasting of safety-critical messages in highly dynamic environments. For vehicular social networks in large scale, socially-aware scalable and reliable data forwarding strategies working in a distributed manner will be devised, with capability of load balancing. For vehicular social networks with selfish nodes, selfishness-tolerant data replication methods will be proposed to guarantee real-time and reliable delivery of important data, by taking into account changing and intermittently-connected vehicular network environments. This project will also propose socially-aware congestion control techniques, which will support service differentiation and improve resource efficiency in vehicular social networks with hybrid data. Expected outcomes will help advance the state of the art and practice of the rapidly emerging area of vehicular social networks.

车载社交网络正在成为新兴的研究热点。高效数据传输是实现车载社交网络应用的重要基础。然而，车载社交网络具有大规模、高动态、高混杂等特征，对数据传输的高效性提出了挑战，许多问题尚待解决。本项目研究适用于车载社交网络的数据传输关键技术，构建一套将社会感知网络化方法作为基本技术架构的高效数据传输技术和方法体系，解决车载社交网络中实时可靠性保障、资源效率优化、区分服务支持等关键科学问题，实现高效的数据传输。为了在高动态时变网络环境下实现紧急消息的实时广播，建立基于时变多层网络理论的广播算法；面向大规模系统环境，建立分布式、可扩展、支持负载均衡、社会感知的可靠数据转发机制；考虑间歇性连通网络条件下节点的自私性，设计自私容忍的数据复制方法，为实时可靠传输提供保障；针对高混杂数据环境，研究支持区分服务、社会感知的拥塞控制技术，提高资源效率。预期成果将为车载社交网络实际应用的发展提供理论和技术支撑。

车载社交网络是一种以车载用户为中心，以车载用户之间的社会关系为基础，深度融合了社交网络与车载网络（即车联网）的移动网络系统。建立高效的数据传输策略是实现车载社交网络应用的重要基础。然而，车载社交网络中的高效数据传输面临巨大挑战。本项目围绕实时可靠数据传输、区分服务支持、高效资源利用等关键科学问题，基于车载网络和社交网络等领域的现有研究成果，以社会感知网络化方法为统一技术架构，研究了社会感知的消息广播算法、数据转发机制、数据复制方法、拥塞控制技术等，初步建立了适用于车载社交网络的数据传输关键技术和方法体系，能够有效提升数据传输的高效性。本项目取得了一系列创新性研究成果，为车载社交网络这一新兴领域的实际应用提供了基础理论和关键技术支撑，在重要国际期刊和会议上发表了一系列高水平学术论文，已经并将继续在国内外产生广泛的影响。